DUV-induced micro and nanopatterning of polymer plasma deposited films

A simple method is described for patterning polymer surfaces with reactive groups. This entails pulsed plasma deposition of anhydride functionalized films, followed by DUV irradiation using a ArF excimer laser. Micro and nano-scale patterning was demonstrated, leading to well defined structures with controlled chemistry and/or geometries. We investigated the chemical changes induced by DUV irradiation. Among other parameters, we demonstrated that the covalent attachment of an amine terminated nucleophile via the aminolysis improved significantly the DUV photosensitivity. Using this approach it was possible to create combinatorial patterned surfaces. In particular such patterned polymer films appear as excellent candidate to study the effect of nanostructuration on the development of biofilms.     

Integrated structure and control design for mechatronic systems with configuration-dependent dynamics

This paper considers the optimal design of mechatronic systems with configuration-dependent dynamics. An optimal mechatronic design requires that, among the structural and control parameters, an optimal choice has to be made with respect to design specifications in the different domains. Two main challenges are treated in this paper: the non-convex nature of the optimization problem and the difficulty in modeling serial machines with flexible components and their embedded controllers. The optimization problem is treated using the direct design strategy which considers simultaneously structural and control parameters as variables and adopts non-convex optimization algorithms. Linear time-invariant and gain-scheduling PID controllers are addressed. This methodology is exploited for the multi-objective optimization of a pick-and-place assembly robot with a gripper carried by a variable-length flexible beam. The resulting design tradeoffs between system accuracy and control efforts demonstrate the advantage of an integrated design approach for mechatronic systems with configuration-dependent dynamics.     

Efficient Scattering Calculations in Complex Backgrounds

The utilization of the Green's tensor associated with a complex optical background (surface, cavity or stratified medium) leads to a dramatic reduction of the computation effort associated with scattering calculations in that background. This approach is illustrated with examples where a mere change of the background Green's tensor makes possible the investigation of completely different physical situations. Two different discretization approaches are compared and similarities between the Green's tensor technique and the Method of Lines are emphasized; in the latter, the utilization of analytic solutions in one specific direction also reduces the discretization of the system.     

Registration and real-time visualization of transcranial magnetic stimulation with 3-D MR images

This paper describes a method for registering and visualizing in real-time the results of transcranial magnetic stimulations (TMS) in physical space on the corresponding anatomical locations in MR images of the brain. The method proceeds in three main steps. First, the patient scalp is digitized in physical space with a magnetic-field digitizer, following a specific digitization pattern. Second, a registration process minimizes the mean square distance between those points and a segmented scalp surface extracted from the magnetic resonance image. Following this registration, the physician can follow the change in coil position in real-time through the visualization interface and adjust the coil position to the desired anatomical location. Third, amplitude of motor evoked potentials can be projected onto the segmented brain in order to create functional brain maps. The registration has subpixel accuracy in a study with simulated data, while we obtain a point to surface root-mean-square error of 1.17+/-0.38 mm in a 24 subject study.     

A patient-mounted robotic platform for CT-scan guided procedures

In this paper, we present a novel robotic assistant dedicated to medical interventions under computed tomography scan guidance. This compact and lightweight patient-mounted robot is designed so as to fulfill the requirements of most interventional radiology procedures. It is built from an original 5 DOF parallel structure with a semispherical workspace, particularly well suited to CT-scan interventional procedures. The specifications, the design, and the choice of compatible technological solutions are detailed. A preclinical evaluation is presented, with the registration of the robot in the CT-scan.     

Adaptive gain and delay mismatch cancellation for LINC transmitter

Linear amplification with Nonlinear Component (LINC) transmitter architecture is an efficient solution for high efficiency amplification of signals. Nonetheless, this solution suffers both from gain impairment and delay mismatch between the two signal paths. Indeed, a mismatch in propagation time between the paths degrades the quality of the transmit signal but also disrupts the convergence of the gain correction algorithm resulting in a degradation of its performance. In this paper, we present an adaptive algorithm based on a gradient descent formulation for the identification and correction of these delays. We also demonstrate its effectiveness when applied prior to the gain adjustment procedure. The identification approach is preferred here, to ensure monitoring facilities.     

JP3D compressed-domain watermarking of still and volumetric medical images

Digital watermarking can be used as data hiding technique to interleave medical images with patient information before transmitting and storing applications. While digital image watermarking and lossy compression methods have been widely studied, much less attention has been paid to their application in medical imaging situations, due partially to speculations on loss in viewer performance caused by degradation of image information. This article describes an hybrid data hiding/compression system, adapted to medical imaging. The central contribution is to integrate blind watermarking, based on turbo trellis-coded quantization, to JP3D encoder. The latter meets conformity condition, with respect to its antecedents JPEG2000 coders. Thus, the watermark embedding can be applied on two-dimensional as well as volumetric images. Results of our method applied to magnetic resonance and computed tomography medical images have shown that our watermarking scheme is robust to JP3D compression attacks and can provide relative high data embedding rate whereas keep a relative lower distortion.     

Measurement of fractional order model parameters of respiratory mechanical impedance in total liquid ventilation

This study presents a methodology for applying the forced-oscillation technique in total liquid ventilation. It mainly consists of applying sinusoidal volumetric excitation to the respiratory system, and determining the transfer function between the delivered flow rate and resulting airway pressure. The investigated frequency range was f ∈ [0.05, 4] Hz at a constant flow amplitude of 7.5 mL/s. The five parameters of a fractional order lung model, the existing "5-parameter constant-phase model," were identified based on measured impedance spectra. The identification method was validated in silico on computer-generated datasets and the overall process was validated in vitro on a simplified single-compartment mechanical lung model. In vivo data on ten newborn lambs suggested the appropriateness of a fractional-order compliance term to the mechanical impedance to describe the low-frequency behavior of the lung, but did not demonstrate the relevance of a fractional-order inertance term. Typical respiratory system frequency response is presented together with statistical data of the measured in vivo impedance model parameters. This information will be useful for both the design of a robust pressure controller for total liquid ventilators and the monitoring of the patient's respiratory parameters during total liquid ventilation treatment.     

Application of the hybrid Hopkins–Abbe method in full-chip OPC

The hybrid Hopkins–Abbe method is presented and shown to resolve the problem of the traditional Hopkins theory, namely the requirement for constant mask diffraction efficiencies. Simulation of electromagnetic scattering from the mask that takes into account the oblique angles of incidence from the illumination is performed by application of the domain decomposition method that is extended for offaxis illumination. Examples of 45 nm and 32 nm lines and spaces through pitch and through focus are presented to demonstrate the validity and accuracy of the hybrid Hopkins–Abbe method. The results obtained are in excellent agreement with a rigorous and independent (third party) simulator.     

A Memristive Nanoparticle/Organic Hybrid Synapstor for Neuroinspired Computing

A large effort is devoted to the research of new computing paradigms associated with innovative nanotechnologies that should complement and/or propose alternative solutions to the classical Von Neumann/CMOS (complementary metal oxide semiconductor) association. Among various propositions, spiking neural network (SNN) seems a valid candidate. i) In terms of functions, SNN using relative spike timing for information coding are deemed to be the most effective at taking inspiration from the brain to allow fast and efficient processing of information for complex tasks in recognition or classification. ii) In terms of technology, SNN may be able to benefit the most from nanodevices because SNN architectures are intrinsically tolerant to defective devices and performance variability. Here, spike‐timing‐dependent plasticity (STDP), a basic and primordial learning function in the brain, is demonstrated with a new class of synapstor (synapse‐transistor), called nanoparticle organic memory field‐effect transistor (NOMFET). This learning function is obtained with a simple hybrid material made of the self‐assembly of gold nanoparticles and organic semiconductor thin films. Beyond mimicking biological synapses, it is also demonstrated how the shape of the applied spikes can tailor the STDP learning function. Moreover, the experiments and modeling show that this synapstor is a memristive device. Finally, these synapstors are successfully coupled with a CMOS platform emulating the pre‐ and postsynaptic neurons, and a behavioral macromodel is developed on usual device simulator.